BP神经网络算法在需水预测与评价中的应用  

Forecasting and Analysis of Water Demand in Jiangxi Province in the Near Future

作　　者：凌和良[1] 桂发亮[2] 楼明珠[3] 

机构地区：[1]南昌工程学院理学系,江西南昌330099 [2]南昌工程学院水利系,江西南昌330099 [3]南昌工程学院计算机科学系,江西南昌330099

出　　处：《数学的实践与认识》2007年第22期42-47,共6页Mathematics in Practice and Theory

基　　金：江西省教育厅科技计划资助项目(赣教技字[2006]256号)

摘　　要：需水预测是进行水资源规划与管理的必备技术方法,在水资源短缺的地区显得尤为重要.合理而准确地预测未来的需水量,可以避免投资的浪费或减少将来用水危机的发生.以江西省为例,采用BP神经网络算法对江西省近期的需水进行预测与评价,将结果与其它方法预测的进行比较,比较结果说明神经网络算法预测需水是成功的。Water demand forecasting is a necessary technology to plan and manage the water resources, it is especial important to many facing the threat of water scarcity regions. How to forecast water demand accurately in avoidance of the waste of investment and water use crisis is very crucial currently. In this paper, take Jiangxi Province as example, we applied BP neural networks algorithm to forecast water demand in Jiangxi Province in the near future, taking the result compared with other forecasting method, the result show that BP neural networks algorithm is successful in water demand forecasting.

关 键 词：水资源 需水预测 神经网络算法 

分 类 号：TV213.4[水利工程—水文学及水资源]